RELATIVE FACTOR ENDOWMENTS AND INTERNATIONAL PORTFOLIO CHOICE

We present a model of international portfolio choice based on cross‐country differences in relative factor abundance. Countries have varying degrees of similarity in their factor endowment ratios, and are subject to aggregate productivity shocks. Risk‐averse consumers can insure against these shocks by investing their wealth at home and abroad. In a many‐good setup, the change in factor prices after a positive shock in a particular country provides insurance to countries that have dissimilar factor endowment ratios, but is bad news for countries with similar factor endowment ratios, since their incomes will worsen. Therefore countries with similar relative factor endowments have a stronger incentive to invest in one another for insurance purposes than countries with dissimilar endowments. The importance of this effect depends on the size of countries. Empirical evidence linking bilateral international equity investment positions to a proxy for relative factor endowments supports our theory: the similarity of host and source countries in their relative capital–labor ratios has a positive effect on the source country’s investment position in the host country. The effect of similarity is enhanced by the size of host countries.     

OPTIMAL PORTFOLIO SELECTION OF BONDS AND STOCKS*

In the present study, we offer an alternative approach to bond portfolio management which differs from the traditional immunization approach. In doing so, we formalize what has been a common practice among some investors who form portfolios of bonds and stocks with a view to optimizing the trade-off between risk and return. By using the general multiindex model to characterize the variance-covariance structure of security returns, both duration theory and modern equilibrium theories of the term structure are incorporated in the analysis. In addition, a simplified selection procedure based on a single-index model is derived. This procedure is intuitively appealing to practitioners since it selects assets on the basis of reward per unit of risk of individual assets.     

QUALITY AND WORK FORCE MANAGEMENT PRACTICES: THE MANAGERIAL PERFORMANCE IMPLICATION

Quality has been in the limelight as organizations have sought to create a competitive advantage and theorists have sought to understand the implications of quality management. This paper examines the synergistic effects of the quality emphasis in the organizations, the use of appropriate work force management practices, and the managerial performance outcomes as interactive phenomena. Using data from multiple levels of employees in manufacturing units in various industries, we tested hypotheses regarding the managerial performance impact of the synergy in work force management practices and the quality emphasis. The results indicate that the effectiveness of work force management practices in enhancing managerial performance varies with the emphasis on quality that is manifested by meeting and exceeding customer needs and preferences through accurate, consistent, reliable, and durable products, and by making design changes in the products as desired by the customer.     

PORTFOLIO MODELS WITH STOCHASTIC CASH DEMAND,BORROWING AND FIXED TRANSFER COSTS

Portfolio models of the Markowitz-Tobin type implicitly assume that the investor does not have to liquidate any part of his portfolio to meet some exogenous cash demand. Since liquidity needs can be an important factor in portfolio management, Chen, Jen, and Zionts [3] in a recent paper developed a model assuming stochastic demand for cash and the possibility of meeting the cash demand by liquidating one or more assets. However, borrowing is an important alternative to liquidating assets. This paper considers that possibility. Unlike Chen, Jen, and Zionts, this paper also considers the more difficult question of liquidation costs being partly fixed and partly variable. In order to make the consideration of borrowing and fixed transfer costs mathematically tractable, the problem is first cast in a framework different from that of [3].     

AUTOCORRELATED CASH FLOWS AND THE SELECTION OF A PORTFOLIO OF CAPITAL ASSETS *

Capital budgeting models for analyzing real assets typically are based on a set of restrictive assumptions that influence financial managers' decisions and may prevent optimization of the firm's objectives. This research examines the common restrictive assumption that cash flows are intertemporally independent by first developing an economic state and simulation model based on a Markov process for including autocorrelated cash flows in the capital budgeting decision process and then demonstrating why managers should include autocorrelated cash flows in capital budgeting models by empirically testing the impact of assuming intertemporally independent cash flows on capital budgeting decisions. The results indicate that ignoring autocorrelated cash flows seriously limits the ability of capital budgeting models to provide optimal investment decisions. The model also is very attractive for practical application because it can be implemented with a minimum number of estimates and provides the set of input data required by a number of capital budgeting models. A discussion of the implementation of the model is included.     

IMPACT OF PARTICIPATION IN THE BUDGETARY PROCESS ON MANAGERIAL ATTITUDES AND PERFORMANCE: UNIVERSALISTIC AND CONTINGENCY PERSPECTIVES*

Data from responsibility-center managers reveal that greater budgetary participation contributes to managerial performance and attitudes in high-environmental-uncertainty situations but hampers performance and attitudes in low-uncertainty situations. Higher budgetary participation reduces managers' propensity to create slack in high- (but not in low-) uncertainty conditions.     

A KNOWLEDGE-BASED DSS FOR MANAGERIAL PROBLEM DIAGNOSIS

A knowledge-based system supporting managerial problem diagnosis is described. The system provides the capability to monitor values of selected variables for problem situations. When problems are located, a list of problem symptoms is delivered to a problem processor for structuring and diagnosis. Problem structuring is based on a combination of concepts from expert systems and structural modeling. User assertions about cause-effect relationships between pairs of variables are maintained in a semantic network. Problem diagnosis uses the relationships in the semantic network to construct causation trees, the branches of which represent potential explanations of the problem symptoms. Mathematical models are constructed based on causation-tree branches, and values from the data base are used to test whether the model confirms the diagnosis. If so, the source of the problem has been located and it is then up to the user to resolve the problem. If the model fails to explain the problem, the model apparently is deficient and the user may perform “what if…” type scenarios in attempts to improve the model and search for problem causes. Realistic applications in the accounting and health care areas are discussed.     

PLANNING MAIL SURVEYS: A MANAGERIAL MODEL

Typically the market research manager faced with implementing a multiple-wave mail survey has certain requirements in terms of response rate, quality, and representativeness. The existing research literature provides some excellent insights into the effects of certain Wave 1 response stimuli. Unfortunately, very little research has been conducted on post-Wave 1 stimuli, and no research has been done on multiple-wave managerial strategy. The authors have developed a prototypic managerial planning model for evaluating various mail survey strategies over multiple-response waves. Subject Areas: Marketing Management and Marketing Research.     

MANAGERIAL USE OF DYNAMIC STRUCTURAL MODELS*

Dynamic structural models were introduced as early as 1958 as “Industrial Dynamics, but there has been little managerial use and little response in the academic world. Yet, the basic modeling methods provide an important mode for examining the broad interacting effects of large systems. More recent work appears to make structural and dynamic models understandable and accessible to individuals not trained in the decision sciences. The nature of the modeling methods is such that managers and policy makers in public systems can be involved directly in the model building process. The authors hope that this survey paper may help rekindle interest.     

PORTFOLIO EVALUATION & RE-EVALUATION: AN EXPERIMENT IN SUBJECTIVE PROBABILITY,MAN-MACHINE LEARNING AND DECISION MAKING

In order to bring home to management science students a proper overview of the field, the author undertakes the investigation of real world problems using the methods of systems analysis and operations research. This paper will describe the results of one such investigation. In addition to describing the classroom experiment, a model for speculative stock market investment will be developed. Finally, a simulation model for reviewing investor performance will be outlined.     

PORTFOLIO MODELING IN MULTIPLE-CRITERIA SITUATIONS UNDER UNCERTAINTY

There have been many models for portfolio selection, but most do not explicitly include uncertainty and multiple objectives. This paper presents an approach that includes these aspects using a form of stochastic integer programming with recourse. The method involves the use of a time-based decision tree structure called a “project tree.” Using this basic format, an illustrative six-project example is presented and analyzed. Various forms of objectives are discussed, ranging from the maximization of expected portfolio value to the maximization of the minimum weighted portfolio deviation from two goals. In each case, formulated numerical problems are given, and the solutions derived are presented. The approach is shown to be very flexible and capable of handling a variety of situations and objectives.     

ISOMORPHISM IN REVERSE: INSTITUTIONAL THEORY AS AN EXPLANATION FOR RECENT INCREASES IN INTRAINDUSTRY HETEROGENEITY AND MANAGERIAL DISCRETION

DiMaggio and Powell (1983) argued that organizations, in their quest for legitimacy, are subjected to isomorphic pressures which produce increasing similarity among peer organizations over time: “Once an organizational field becomes well established ... there is an inexorable push toward homogenization.” Yet, in contradiction to this “iron cage” hypothesis, many industries became more heterogeneous, not more homogeneous, in their profiles during the latter decades of the twentieth century, particularly between about 1980 and 2000 (at least on the American landscape). Why didn’t “inexorable homogenization” occur? We argue that DiMaggio and Powell were correct about the forces that give rise to isomorphism but failed to anticipate several major macrosocial trends that caused those forces all to move in directions that diminished, rather than accentuated, isomorphism. For example, DiMaggio and Powell argued that ambiguity about goals will propel isomorphic change; but the goals for publicly-traded U.S. corporations became less ambiguous. They hypothesized that the fewer the alternative organizational models in a field, the faster the rate of isomorphism; but the array of organizational models increased significantly. We empirically illustrate the increased heterogeneity that occurred within American industries by tracing the trend toward divergence – on several dimensions of strategy and performance – within the steel industry. An analysis of 18 additional industries similarly yields far more evidence of increased heterogeneity than of increased homogeneity over the latter decades of the twentieth century. We go on to argue that reduced isomorphic pressures not only engendered greater intraindustry variety, but also increased managerial discretion, which contributed greatly to the romanticization of CEOs that occurred during the period 1980–2000.     

PORTFOLIO MODELING IN MULTIPLE-CRITERIA SITUATIONS UNDER UNCERTAINTY: COMMENT

In a recent issue of Decision Sciences, Muhlemann, Lockett, and Gear [8] developed a multiple-objective, stochastic linear programming formulation of the multiperiod portfolio selection problem under uncertainty. The purpose of this note is to offer some extensions to their multicriteria approach which is otherwise viewed as an excellent attempt at modeling realistic aspects of the portfolio selection problem. Further, integer goal programming combined with simulation is suggested as an alternate approach for solving the dynamic multiple-objective problem.     

OPTIMAL PORTFOLIO SELECTION WITH UPPER BOUNDS FOR INDIVIDUAL SECURITIES*

In this paper, we consider optimal portfolio selection with no short sales and with upper bounds for individual securities. The solution is reached by directy revising the optimal portfolio without upper bounds. Specifically, our analysis is based on the single-index model, as well as the general multi-index model that provides the return generating process for securities in the arbitrage pricing theory. As demonstrated in a simulation study, the proposed algorithm for optimal portfolio selection usually requires very few iterations. Also, since our approach is developed using intuitive reasoning and simple linear algebra, we are able to provide direct and intuitive justifications for the resulting portfolio choice. Therefore this paper should be of interest to both finance academics and practitioners in portfolio management.     

THE APPLICABILITY OF THE MAXI–MIN PRINCIPLE TO PORTFOLIO SELECTION IN TERMS OF MEANS AND VARIANCES OF UNKNOWN DISTRIBUTIONS

This paper establishes two propositions which allow a risk-a verse decision maker to apply a maxi-min strategy in his portfolio selection. The strategy consists of selecting a portfolio in which the lower bound of the expected utility is maximized. The propositions have their greatest applicability in situations in which the investor knows the means and variances of the portfolio returns, but has no other knowledge relating to the probability distributions governing the rates of return.     

EFFECTS OF CONFLICTING ANALYSES ON MANAGERIAL DECISION MAKING: A LABORATORY EXPERIMENT

Researchers in a variety of disciplines have recommended the use of multiple conflicting data analyses to improve managerial decision making through the challenging of assumptions. This study deals with the effects of single data analyses and conflicting analyses on managers' solutions to a case analysis task. Results showed that managers who received conflicting analyses produced solutions with higher expected profits than those who received single analyses. Implications for the use of analytic decision aids are noted.     

AN ANALYSIS OF PORTFOLIO REVISION STRATEGIES UTILIZING VARIABLE REVISION INTERVALS*

This paper investigates portfolio revision with an emphasis on the decision of when to revise. A statistical technique based on the sequential analysis of the time series of portfolio return relatives determines when revision is to occur. The technique detects changes in the time series which are an indication that the underlying generating process of the time series has changed and that the portfolio should be, if necessary, revised. Thus, the length of the revision interval is variable and a function of the data. The statistical technique is utilized in conjunction with three portfolio revision strategies. These three revision strategies are compared to a buy and hold policy over three nonoverlapping, 12-year investment horizons. The basis of comparison is the net terminal values which include adjustments for transaction costs and taxes. The sensitivity of the statistical technique to its parameters is also analyzed.     

A NOTE ON OPTIMAL PORTFOLIO SELECTION UNDER STABLE PARETIAN DISTRIBUTIONS*

Elton, Gruber, and Padberg's [2] [3] ranking procedure and Kwan's [6] nonranking procedure for optimal portfolio selection lead to the same solution. This is because of a particular functional property of the cutoff rate for security performance. In this note, the robustness of that functional property is demonstrated the normality of security returns assumed in the above studies is relaxed to encompass the general family of stable Paretian distributions. The proof here is an important step toward portfolio analysis using some multiindex models when securities cannot be ranked.